Non-Linear Time Series Models in Empirical Finance [Paperback]

Philip Hans Franses (Author), Dick van Dijk (Author)

Book Description

Publication Date: September 4, 2000 | ISBN-10: 0521779650 | ISBN-13: 978-0521779654 | Edition: 1

This is the most up-to-date and accessible guide to one of the fastest growing areas in financial analysis by two of the most accomplished young econometricians in Europe. This classroom-tested advanced undergraduate and graduate textbook provides an in-depth treatment of recently developed nonlinear models, including regime-switching and artificial neural networks, and applies them to describing and forecasting financial asset returns and volatility. It uses a wide range of financial data, drawn from sources including the markets of Tokyo, London and Frankfurt.

Editorial Reviews

Book Description

The most up to-date and accessible guide to one of the fastest growing areas in financial analysis by two of the most accomplished young econometricians in Europe. This classroom-tested advanced undergraduate and graduate textbook provides an in-depth treatment of recently developed non-linear models, including regime-switching and artificial neural networks, and applies them to describing and forecasting financial asset returns and volatility. Uses a wide range of financial data, drawn from sources including the markets of Tokyo, London and Frankfurt.

Product Details

• Paperback: 298 pages
• Publisher: Cambridge University Press; 1 edition (September 4, 2000)
• Language: English
• ISBN-10: 0521779650
• ISBN-13: 978-0521779654
• Product Dimensions: 9.6 x 6.8 x 0.8 inches
• Shipping Weight: 1.4 pounds (View shipping rates and policies)
• Average Customer Review: 4.9 out of 5 stars  See all reviews (7 customer reviews)
• Amazon Best Sellers Rank: #374,510 in Books (See Top 100 in Books)

More About the Author

Discover books, learn about writers, read author blogs, and more.

Customer Reviews

Most Helpful Customer Reviews

38 of 38 people found the following review helpful:

5.0 out of 5 stars An excellent, up-to-date guide of finance non-linear models, August 22, 2001

By 

Daniel Ventosa S (Marseille, France) - See all my reviews

This review is from: Non-Linear Time Series Models in Empirical Finance (Paperback)

If you are interested in what's up nowadays in the finance modeling, you should have this book. It's a review of some of the more recent, important and promising works of the field. Advanced undergraduate students and graduate students will probably understand the book (although I recommend it mostly for people interested in the field). If you want an easy introduction of most of the topics (but pretty older), then, grab Walter Enders book or, the more complicated, but also more complete book of James D. Hamilton. Reading this manual is easy because it's clear and its style is not boring. If you really love finance econometrics, you'll find this book fun to read. The fields covered by the authors are: 1.-Linear models (pretty brief), unit roots, seasonality and aberrant observations; 2.-Regime-switching models for returns such as TAR (Threshold Autoregressive), SETAR,...; 3.-Regime switching models for volatility (and here you'll have the entire family of ARCH models, with its youngest cousins such as GARCH QGARCH, LSTGARCH, VS-GARCH); 4.-Artificial Neural Network for returns. I'm particularly interested in GARCH-type models, and I can tell this part is particularly well done. At the end of the chapter there is a very illuminating empirical comparison between the models. I cannot say if the "artificial neural networks" is a good chapter since I'm not an expert, but the least I can say is that it's pretty understandable (although quite challenging for an ignorant like myself).

31 of 32 people found the following review helpful:

4.0 out of 5 stars A timely survey on an important area, January 9, 2001

By 

Random Thoughts (Maryland) - See all my reviews

Amazon Verified Purchase

This review is from: Non-Linear Time Series Models in Empirical Finance (Hardcover)

The title of this book caught my attention immediately and it actually contains more interesting topics than I thought. After I bought a copy through Amazon and have a closer read, I'm not disapointed by the two authors' writing, which is probably partially based on the second author's PhD dissertation, and so it is a little narrow-focused. But as the authors stated, they want to produce a book which deals with nonlinear techniques as opposed to Mills's mostly linear methods in fiance time series. They have delivered. With hot topics such as regime switching, ARCH models, and neural network applications in finance, I'm sure this book will find a lot of interested readers and will be a key reference in nonlinear empirical finance.

23 of 23 people found the following review helpful:

5.0 out of 5 stars nice coverage of time series methods applicable to finance, February 6, 2008

By 

Michael R. Chernick "statman31147" (Holland PA) - See all my reviews
(REAL NAME)   

This review is from: Non-Linear Time Series Models in Empirical Finance (Paperback)

Like his other books, Franses provides an nice applied treatment of non-linear time series models that are in this case applicable to finance. It includes extensive coverage of regime switching models. It includes data drawn from several financial markets including Tokyo, London and Frankfurt.